Recent Research Research Articles

Advancements in machine learning for predicting phases in high-entropy alloys: a comprehensive review

High entropy alloys (HEAs) are distinguished by their enhanced physicochemical properties, attributed to the formation of various phases such as solid solution (SS), intermetallic (IM), or a combination (SS + IM). These phases contribute distinctively to the microstructure of the alloys. A critical aspect of alloy design revolves around accurately predicting these phases, which has led to the integration of sophisticated data vetting methods and Machine Learning (ML) algorithms in recent research. This review paper aims to provide a comprehensive analysis of the advancements in phase prediction accuracy within HEAs, an essential component in the development of these alloys. HEAs are known for their intricate compositions, offering a wide spectrum of material properties, making them particularly relevant for applications aimed at future sustainability. Phase engineering in HEAs unlocks the potential for creating materials tailored to eco-friendly technologies and energy-efficient solutions. The challenge in predicting phase selection in HEAs is accentuated by the limited data available on these complex materials. This review delves into how advanced data vetting techniques and ML algorithms are being employed to overcome these challenges, thus contributing significantly to sustainable material design. The paper examines various algorithms used in HEA phase prediction, including KNN (K-Nearest Neighbors), SVM (Support Vector Machines), ANN (Artificial Neural Networks), GNB (Gaussian Naive Bayes), and RF (Random Forest). It discusses the testing accuracy of these algorithms in classifying HEA phases, revealing variations in their effectiveness. The review highlights the superior accuracy of ANNs, followed closely by KNN and SVM, while noting the comparatively lower accuracy of GNB. This comprehensive review synthesizes current research efforts in utilizing computational methods to design HEAs, underlining their broader implications in expediting the discovery and development of diverse metal alloys. These efforts are pivotal in meeting the evolving demands of modern engineering applications, thereby contributing to the advancement of materials science.

Traditional Uses, Phytochemical Constituents and Ethnopharmacological Properties of Mistletoe from Phoradendron and Viscum Species.

Plants from the genus Phoradendron and Viscum, also known as American and European mistletoe, are a group of hemiparasitic plants traditionally used to treat many diseases. Mistletoes have a rich content of natural compounds like terpenes, alkaloids, proteins, and phenolic compounds associated with their potential medicinal properties. In this sense, mistletoes have shown antiproliferative, antioxidant, anti-inflammatory, and antimicrobial activity, which has been attributed to their phytochemical constituents. The mechanisms in which mistletoe plants act vary and depend on their phytochemical content and distribution, which in part will depend on the mistletoe species. In this sense, recent literature research is needed to visualize state of the art in the ethnopharmacological potential of mistletoe. Thus, this literature review aims to systematically report recent studies (2010-2023) on the phytochemical characterization and bioactive studies of mistletoe plants, mainly the Viscum and Phoradendron genera. We gather recent information of 161 references selected in our research. Here we report that although there are several bioactivity studies of mistletoe species, bioavailability studies are still scarce, and the precise mechanisms of action are not fully known. We encourage that further studies include a systematic strategy to cover these areas of opportunity.

A current study of psychological well-being in educational institutions: A systematic literature review

The issue of psychological well-being in education has emerged as an increasingly critical topic in recent years. This is due to the significance of psychological well-being in enhancing the performance of e ducational institutions, encompassing students, teachers, and the process of formulating school policies. This study sought to discover recent research on psychological well-being from an academic perspective. A total of 27 research articles were successfully gathered and reviewed based on the established criteria. This article review was conducted utilizing two databases (SCOPUS and WoS) and the following keywords: "psychological well-being" combined with "AND" and other search terms such as "school", "teacher", and "student". This systematic review offers a synthesis of results that can serve as the initial step in developing constructs of psychological well-being in educational institutions, thus implying the importance of psychological well-being for teachers and students. The results of the analysis from this systematic literature review have been discussed and concluded in this study.

High-Throughput Sequencing Technology Assisted Investigation of the Correlation between Intestinal Flora, Serum Biochemistry, Blood Lipids, and Tumour Markers in Patients with Gastric Cancer and Healthy Plateau Residents.

Aim The goal is to use high-throughput sequencing technology to compare and study the structure and variety of intestinal flora in people with gastric cancer and healthy people in the Qinghai-Tibet Plateau. Background Recent research has connected gut flora structure to numerous disorders. Metabolites, endotoxins, and immunomodulatory modulation might cause gastrointestinal or other systemic diseases and affect gastric cancer treatment and prognosis. We used the correlation study to uncover biomarkers associated with good intestinal flora and gastric cancer groups on the plateau to investigate their involvement in gastric cancer development. Objectives To investigate the possible links between intestinal flora and gastric cancer in the Qinghai Plateau region using a variety of clinical phenotypic data and to investigate the flora that may be linked to gastric cancer. Methods The 22 Qinghai Province tertiary hospital gastric cancer patients and 30 healthy people had their fresh faeces collected. To examine intestinal flora diversity and composition, 52 patients underwent 16S rDNA high-throughput gene sequencing of intestinal bacteria. The correlation between clinical phenotypes and the top 15 dominant intestinal flora at the phylum level was analyzed. Results The difference in total protein TP between the healthy group and the gastric cancer group was statistically significant (P<0.001). Globulin was significantly different (P<0.05), TC of total cholesterol was significantly different (P<0.05). High-density lipoprotein showed statistical significance (P<0.05).The difference in low-density lipoprotein was statistically significant (P<0.001). Alpha-fetoprotein was significantly different (P<0.05). CA72-4 carbohydrate antigen (P<0.05). Conclusion There were significant differences in total protein, globulin, total cholesterol, high density lipoprotein, low-density lipoprotein, alpha-fetoprotein and carbohydrate antigen CA72-4 in patients with gastric cancer in the plateau area compared with the healthy group, and the different clinical variables were correlated with intestinal flora at some phylum and genus levels.

Current Advances in Production and Drying Technologies of Lactoferrin

Lactoferrin, a multifunctional iron-binding glycoprotein present in milk, exhibits a remarkable array of beneficial properties, including antibacterial, anticancer, antiviral, antioxidant, and anti-inflammatory effects. Its potential as a novel food and nutritional supplement has sparked substantial interest among researchers and the industry. This review summarizes the recent research progress on the physiological functions of lactoferrin, and summarizes various technological advances in the separation and purification of lactoferrin. Furthermore, it conducts a detailed comparative analysis of various production and drying methods, providing fresh insights and a robust theoretical framework for advancing lactoferrin-related applications. The development of cost-effective and efficient lactoferrin production techniques holds paramount importance, as it plays a pivotal role in accelerating industrial lactoferrin production and driving growth in the dairy industry.

A Review on Soft Exoskeletons for Hand Rehabilitation

Background: How to enhance the quality of life for the elderly has emerged as a key issue in many nations due to the ageing population. Stroke is the most prevalent disease among the elderly; specifically, the hand dysfunction caused by stroke is also a powerful obstacle to the daily life of the elderly. Soft Exoskeletons for Hand Rehabilitation (SEHRs) have become a major trend for the future due to the increasing demand for hand rehabilitation. Objective: To provide a reference for readers in this field by introducing the most recent research developments in the field of SEHR, including their classification and properties. Methods: By reviewing different types of hand rehabilitation exoskeleton research papers and patents, the advantages and disadvantages, differences, and applications of various SEHRs were summarized. Results: According to the driving mode and realizing the function of SEHRs, the structure characteristics of SEHRs are analyzed and compared. The key problems and future development trends of SEHRs were expounded. Conclusion: According to the driving method, the research shows that SEHRs can be divided into Air-Driven Soft Exoskeletons for Hand Rehabilitation (ADSEHRs), Motor-Driven Soft Exoskeletons for Hand Rehabilitation (MDSEHRs), and Hybrid-Driven Soft Exoskeletons for Hand Rehabilitation (HDSEHRs). Future research is required to further optimize the flexibility and adaptability of soft exoskeletons, improve their accuracy and sensitivity, and enhance human-machine interaction with the human hand.

A study on the significance of serine hydroxymethyl transferase expression and its role in bladder cancer

Bladder cancer (BLCA) is a common malignant tumor in urinary system all over the world. However, due to its high recurrence rate and complex causes, clinicians often have limited options for surgical and drug treatments. Recent researchs on the molecular mechanism of BLCA have reveals its biological progress and potential for early diagnosis. Serine hydroxymethyltransferase 1/2 (SHMT1/2) is a crucial enzyme in the one-carbon metabolism of tumor cells, and the expression levels of these isozymes have been found to be associated with the biological progression of various malignant tumors. However, the impact of SHMT1/2 on the biological progression of bladder cancer and its molecular regulation mechanism remain unclear. In this research utilizes BLCA clinical sample data, the TCGA database, and in vitro cell experiments to predict the expression levels of SHMT1/2 in BLCA. The findings indicate that SHMT1 remained unchanged, while SHMT2 expression is increased in BLCA, which was related to poor prognosis. Additionally, SHMT2 affects the growth, migration, and apoptosis of bladder cancer cells in vitro. It also influences the expression levels of E-cadherin and N-cadherin, ultimately impacting the malignant biological progression of bladder tumors. These results establish a correlation between SHMT2 and the malignant biological progression of BLCA, providing a theoretical basis for the early diagnosis and treatment of bladder cancer.

Quantitative Ultrasound Spectroscopy for Screening Cylindrical Lithium‐Ion Batteries for Second‐Life Applications

AbstractDiagnosing lithium‐ion battery degradation is a crucial part of managing energy storage systems. Recent research has explored ultrasonic testing for non‐invasive health assessment as an alternative to traditional, time‐consuming, electrical‐only methods. Assessing the state of health is vital for determining quality at end of ‘first’ life, with retired batteries at 70–80 % health still holding value for secondlife applications. Over the coming years, tens of GWh of salvaged batteries will hit the market, requiring rapid noninvasive methods to classify retired batteries according to their state of health. This study uses a 64 – element ultrasonic array to obtain mid‐band quantitative ultrasound spectroscopy parameters – including mid‐band fit, spectral slope, and intercept – from circumferential waves around cylindrical batteries. Thirteen cylindrical cells were used to evaluate the methodology: three pristine and ten retired from the same source. The mid‐band fit showed the ability to track the state of charge and discriminate between the state of health levels in accelerated degradation experiments both with pristine batteries, and also with recovered secondlife batteries with unknown historical use. Linear‐array ultrasonic transducers, coupled with quantitative spectral parameters, show promise for future non‐destructive battery health screening methods, offering valuable insights for the emerging used battery market.

Bridging the Mind and Gut: Uncovering the Intricacies of Neurotransmitters, Neuropeptides, and their Influence on Neuropsychiatric Disorders.

The gut-brain axis (GBA) is a bidirectional signaling channel that facilitates communication between the gastrointestinal tract and the brain. Recent research on the gut-brain axis demonstrates that this connection enables the brain to influence gut function, which in turn influences the brain and its cognitive functioning. It is well established that malfunctioning of this axis adversely affects both systems' ability to operate effectively. Dysfunctions in the GBA have been associated with disorders of gut motility and permeability, intestinal inflammation, indigestion, constipation, diarrhea, IBS, and IBD, as well as neuropsychiatric and neurodegenerative disorders like depression, anxiety, schizophrenia, autism, Alzheimer's, and Parkinson's disease. Multiple research initiatives have shown that the gut microbiota, in particular, plays a crucial role in the GBA by participating in the regulation of a number of key neurochemicals that are known to have significant effects on the mental and physical well-being of an individual. Several studies have investigated the relationship between neuropsychiatric disorders and imbalances or disturbances in the metabolism of neurochemicals, often leading to concomitant gastrointestinal issues and modifications in gut flora composition. The interaction between neurological diseases and gut microbiota has been a focal point within this research. The novel therapeutic interventions in neuropsychiatric conditions involving interventions such as probiotics, prebiotics, and dietary modifications are outlined in this review. The findings of multiple studies carried out on mice show that modulating and monitoring gut microbiota can help treat symptoms of such diseases, which raises the possibility of the use of probiotics, prebiotics, and even dietary changes as part of a new treatment strategy for neuropsychiatric disorders and their symptoms. The bidirectional communication between the gut and the brain through the gut-brain axis has revealed profound implications for both gastrointestinal and neurological health. Malfunctions in this axis have been connected to a range of disorders affecting gut function as well as cognitive and neuropsychiatric well-being. The emerging understanding of the role of gut microbiota in regulating key neurochemicals opens up possibilities for novel treatment approaches for conditions like depression, anxiety, and neurodegenerative diseases.

A Comprehensive Review on Potential Molecular Drug Targets for the Management of Alzheimer's Disease.

Alzheimer's disease (AD) is an onset and incurable neurodegenerative disorder that has been linked to various genetic, environmental, and lifestyle factors. Recent research has revealed several potential targets for drug development, such as the prevention of Aβ production and removal, prevention of tau hyperphosphorylation, and keeping neurons alive. Drugs that target numerous ADrelated variables have been developed, and early results are encouraging. This review provides a concise map of the different receptor signaling pathways associated with Alzheimer's Disease, as well as insight into drug design based on these pathways. It discusses the molecular mechanisms of AD pathogenesis, such as oxidative stress, aging, Aβ turnover, thiol groups, and mitochondrial activities, and their role in the disease. It also reviews the potential drug targets, in vivo active agents, and docking studies done in AD and provides prospects for future drug development. This review intends to provide more clarity on the molecular processes that occur in Alzheimer's patient's brains, which can be of use in diagnosing and preventing the condition.

Neuroendocrinological and Clinical Aspects of Leptin.

Obesity is characterized by an abnormal increase in adipose tissue mass and is regarded as a neurobehavioral as well as a metabolic disorder. Increases in body fat are caused by even slight, long-term discrepancies between energy intake and energy expenditure. It is a chronic condition linked to the metabolic syndrome, a spectrum of risky conditions, such as diabetes, high blood pressure, and heart disease. With a swiftly rising prevalence, obesity has emerged as a significant global health concern. Leptin influences the brain's neuroendocrine and metabolic processes, which is important for maintaining energy homeostasis. White adipose tissue secretes the majority of leptin, and there is a positive correlation between leptin levels in the blood and body fat percentages. The central nervous system is also modulated by leptin levels to modify energy intake and usage. The idea of an obesity cure sparked excitement after it was discovered more than 25 years ago. However, the leptin medication only effectively reduces weight in patients with congenital leptin insufficiency and not in patients with typical obesity who may also have leptin resistance. Recent research has focused on the role of leptin in managing weight reduction and preventing "yo-yo dieting." This review concentrates on the neurological effects of leptin with a focus on therapeutic and diagnostic applications, particularly for childhood obesity.

Sentiment analysis with hotel customer reviews using FNet

Recent research has focused on opinion mining from public sentiments using natural language processing (NLP) and machine learning (ML) techniques. Transformer-based models, such as bidirectional encoder representations from transformers (BERT), excel in extracting semantic information but are resourceintensive. Google’s new research, mixing tokens with fourier transform, also known as FNet, replaced BERT’s attention mechanism with a non-parameterized fourier transform, aiming to reduce training time without compromising performance. This study fine-tuned the FNet model with a publicly available Kaggle hotel review dataset and investigated the performance of this dataset in both FNet and BERT architectures along with conventional machine learning models such as long short-term memory (LSTM) and support vector machine (SVM). Results revealed that FNet significantly reduces the training time by almost 20% and memory utilization by nearly 60% compared to BERT. The highest test accuracy observed in this experiment by FNet was 80.27% which is nearly 97.85% of BERT’s performance with identical parameters.

Recent Research on Magnetic Machinery

Background: As a clean energy source, magnetic energy is a significant power source of mechanical equipment, which affects the direction of control mode and mechanical structure of mechanical equipment. Magnetic machinery is widely used in industrial power systems and automatic control systems as the power source of mechanical equipment transmission parts or actuators. Magnetic machinery is essential to make mechanical equipment easy to control, energy saving and environmental protection, simple structure, and so on. In order to innovate the control mode of mechanical equipment and optimize the types of traditional mechanical systems, magnetic machinery developed magnetic coupling, magnetic gear, magnetic spring, and other magnetic machinery. The characteristics of magnetic machines with different functions are analyzed based on the types of magnetic machines. Therefore, this aspect's development and application are getting more attention in recent years. To innovate the control mode of mechanical equipment and optimize the types of traditional mechanical structures, magnetic types of machinery, such as magnetic coupling, magnetic gear, and magnetic spring, are making continuous progress. New magnetic machines are also being developed. This paper summarizes the typical patents on three kinds of magnetic machinery: magnetic coupling, magnetic gear and magnetic spring. In addition, the advantages of existing magnetic machinery are summarized, the current situation of magnetic machinery is analyzed, and the development of magnetic machinery is summarized. Through the analysis of enormous patents of magnetic coupling, magnetic gear, and magnetic spring, it is concluded that although there are many kinds of magnetic machinery, there are no systematic and mature design theories and methods. The development trend of magnetic machinery is also discussed. The research on magnetic machinery helps innovate mechanical equipment's control mode and optimize the types of traditional mechanical structures. As a result, more patents will be invented in the future.

Ebselen: A Review on its Synthesis, Derivatives, Anticancer Efficacy and Utility in Combating SARS-COV-2.

Ebselen is a selenoorganic chiral compound with antioxidant properties comparable to glutathione peroxidase. It is also known as 2-phenyl-1,2-benzisoselenazol-3(2H)-one. In studies examining its numerous pharmacological activities, including antioxidant, anticancer, antiviral, and anti-Alzheimer's, ebselen has demonstrated promising results. This review's primary objective was to emphasize the numerous synthesis pathways of ebselen and their efficacy in fighting cancer. The data were collected from multiple sources, including Scopus, PubMed, Google Scholar, Web of Science, and Publons. The starting reagents for the synthesis of ebselen are 2-aminobenzoic acid and N-phenyl benzamide. It was discovered that ebselen has the ability to initiate apoptosis in malignant cells and prevent the formation of new cancer cells by scavenging free radicals. In addition, ebselen increases tumor cell susceptibility to apoptosis by inhibiting TNF-α mediated NF-jB activation. Ebselen can inhibit both doxorubicin and daunorubicin-induced cardiotoxicity. Allopurinol and ebselen administered orally can be used to suppress renal ototoxicity and nephrotoxicity. Due to excessive administration, diclofenac can induce malignancy of the gastrointestinal tract, which ebselen can effectively suppress. Recent research has demonstrated ebselen to inhibit viral function by binding to cysteine-containing catalytic domains of various viral proteases. It was discovered that ebselen could inhibit the catalytic dyad function of Mpro by forming an irreversible covalent bond between Se and Cys145, thereby altering protease function and inhibiting SARS-CoV-2. Ebselen may also inhibit the activation of endosomal NADPH oxidase of vascular endothelial cells, which is believed to be required for thrombotic complications in COVID-19. In this review, we have included various studies conducted on the anticancer effect of ebselen as well as its inhibition of SARS-CoV-2.

A novel thermal bus architecture for large cryogenic space telescopes utilizing helium pulsating heat pipes

Future space telescopes, such as those proposed for the Far-infrared Surveyor Mission, are expected to employ actively cooled optical arrays with a similar overall surface area compared to the James Webb Space Telescope. Therefore, there is a need for a cryogenic cooling system with a thermal bus architecture that can distribute cooling to these large optical arrays. Recent experimental research of helium Pulsating Heat Pipes (PHPs) has shown that helium PHPs can transfer heat over long distances (on the order of 2 m) with high efficiency, and also have the ability to act as a passive thermal switch upon the removal of the cooling source. PHPs’ high thermal performance, passive switching capability, low mass, and ease of manufacturing make them an appealing option compared to high-purity metal straps for a thermal bus architecture on large cryogenic space telescopes. A novel architecture for the thermal control of optical arrays is proposed utilizing unique configurations of helium pulsating heat pipes that minimize mass, maximize thermal performance, and reduce the risk of mission failure.

Identification and Measurement of Biomarkers at Single Microorganism Level for In Situ Monitoring Deep Ultraviolet Disinfection Process.

Since the COVID-19 disease has been further aggravated, the prevention of pathogen transmission becomes a vital issue to restrain casualties. Recent research outcomes have shown the possibilities of the viruses existing on inanimate surfaces up to few days, which carry the risk of touch propagation of the disease. Deep ultraviolet germicide irradiation (UVGI) with the wavelength of 255-280nm has been verified to efficiently disinfect various types of bacteria and virus, which could prevent the aggravation of pandemic spread. Even though considerable experiments and approaches have been applied to evaluate the disinfection effects, there are only few reports about how the individual bio-organism behaves after ultraviolet C (UVC) irradiation, especially in the aspect of mechanical changes. Furthermore, since the standard pathway of virus transmission and reproduction requires the host cell to assemble and transport newly generated virus, the dynamic response of infectious cell is always the vital aspect of virology study. In this work, high power LEDs array has been established with 270nm UVC irradiation to evaluate disinfection capability on various types of bio-organism, and incubator embedded atomic force microscopy (AFM) is used to investigate the single bacterium and virus under UVGI. The real-time tracking of the living Vero cells infected with adenovirus has also been presented in this study. The results show that after sufficient UVGI, the outer shell of bacteria and viruses remain intact in structure, however the bio-organisms lost the capability of reproduction and normal metabolism. The experiment results also indicate that once the host cell is infected with adenovirus, the rapid production of newborn virus capsid will gradually destroy the cellular normal metabolism and lose mechanical integrity.

Neural Stem Cell-based Regenerative Therapy: A New Approach to Diabetes Treatment.

Diabetes mellitus (DM) is the most common metabolic disorder that occurs due to the loss, or impaired function of insulin-secreting pancreatic beta cells, which are of two types - type 1 (T1D) and type 2 (T2D). To cure DM, the replacement of the destroyed pancreatic beta cells of islet of Langerhans is the most widely practiced treatment. For this, isolating neuronal stem cells and cultivating them as a source of renewable beta cells is a significant breakthrough in medicine. The functions, growth, and gene expression of insulin-producing pancreatic beta cells and neurons are very similar in many ways. A diabetic patient's neural stem cells (obtained from the hippocampus and olfactory bulb) can be used as a replacement source of beta cells for regenerative therapy to treat diabetes. The same protocol used to create functional neurons from progenitor cells can be used to create beta cells. Recent research suggests that replacing lost pancreatic beta cells with autologous transplantation of insulin-producing neural progenitor cells may be a perfect therapeutic strategy for diabetes, allowing for a safe and normal restoration of function and a reduction in potential risks and a long-term cure.

Perceptions and Socioeconomic Status Influence Purchases of Native Plants

Plants native to the United States, defined as those being present before European settlement, have aesthetic and environmental benefits. In 2018, only 10% of plant sales were native plants, a plant category that tends to be underrepresented in many residential and commercial landscapes. Although earlier research indicated that consumers find native plants less aesthetically appealing relative to introduced species, more recent research reported a growing demand for native plants. Thus, a better understanding of consumer perceptions would facilitate their marketing. We used an online survey of 1824 participants representing five geographic regions (West, Southwest, Midwest, Southeast, and Northwest) to classify adopters based on their purchase of native plants. A double-hurdle model was used to estimate factors influencing purchasing native plants among US homeowners, and the factors influencing the amount spent on native plants in 2021. Demographically, metropolitan, college-educated, and younger participants were more likely to be native plant adopters; they also spent 80% more on plants compared with nonnative plant adopters. More native plant adopters agreed that native plants were better for the environment than exotic plants (68%), are readily available in their area (67%), and are better adapted to difficult sites (75%). Marketing efforts should capitalize on the environmental benefits to stimulate purchases.

Model Predictive Control of Magnetic Helical Swimmers in Two-Dimensional Plane

Magnetic micro/mini-swimmers have a great potential application in biomedical research and have gained broad attention. Recent research studies focus on the automatic control methods of magnetic micro/mini-swimmers, such as artificial intelligence methods. However, their autonomous manipulation remains a challenge since they are subject to various disturbances from the external environment and model uncertainties. The current methods employ a status observer to estimate these disturbances and uncertainties. In this paper, we apply a data-driven technique that utilizes the nonlinear approximation ability of neural networks (NNs). To be specific, a flexible structure of NNs, Broad Learning System (BLS), is employed to model the input-output mapping relationship between the direction of the rotating magnetic field and the swimming direction of the helical miniature swimmer. Then, according to the dual-variable decoupling control, a levitation controller is formulated and a path following controller is proposed based on a planar three-degree-of-freedom model of magnetic helical swimmers, which is inspired by the model of wheeled mobile robots. Simulations and experiments are conducted to quantitatively validate the proposed control method using different planar paths. The experiment results show that the mean absolute error of the path following control is about 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\%$</tex-math> </inline-formula> of the body length which is less than 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$mm$</tex-math> </inline-formula> . Our proposed control method provides a preliminary study to alleviate the impact of disturbances and uncertainties on the control performance of magnetic micro/mini-swimmers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is mainly motivated by the potential application of artificial intelligence methods in magnetic micro/mini-robot community, especially for the applications that reject disturbances and uncertainties. In practice, a path planner is employed to compute a pre-defined reference path that connects the start and the targeted locations. Then our control method is applied to the magnetic helical swimmer and it is guided to follow the reference path. Tackling external disturbances and model uncertainties is still challenging during the control progress. Neural network-based technique is an intuitive approach since their nonlinear modeling ability and generalization are suitable for estimating these disturbances and uncertainties. As for training the neural-network model, the training data about the angle parameters should be recorded by manual control of the helical swimmer. These angle parameters define the rotating axis of the uniform rotating magnetic field and the self-rotating axis of the magnetic helical swimmer. According to the planar motion model, the optimal controller is formulated using the feedback distance error and angle error, and the sum of the control signal and the prediction of the compensating model is used as the final control input. Our electromagnetic coil system features easy operation and configuration of cameras or other sensors. Simulations and experiments validate the performance of the neural network-based compensating method and the proposed optimal control method using magnetic micro/mini-swimmers.

Mechanical characterization of materials using advanced microscopy techniques

This review explores the synergistic relationship between advanced microscopy techniques and mechanical engineering, outlining their profound impact on materials science and mechanical system design. We delve into the multifaceted applications of electron microscopy, X-ray diffraction, and spectroscopic methods in understanding microstructural dynamics, mechanical properties, and failure mechanisms of materials integral to mechanical engineering. Through a comprehensive synthesis of recent research, we emphasize the pivotal role these techniques play in optimizing material performance, bolstering structural integrity, and driving innovation in mechanical design. By elucidating the intricate details of material behavior at the microscale, advanced microscopy contributes to informed decision-making in material selection and design processes. Furthermore, we address emerging trends and prospects, underscoring the continued synergy between advanced microscopy and mechanical engineering. This collaboration remains at the forefront of materials science and technology, promising ongoing advancements that will shape the future landscape of mechanical design and materials innovation.